Senior Data Scientist (Discovery)
Posted Updated
Description
- As a Data Scientist, you will own the ranking initiatives that power these canvases. You aren’t just building models; you are building the economic and social frameworks that decide which experiences thrive
- You will report directly to the Senior Director of Data Science and serve as a high-visibility IC leader driving the roadmap for our most critical consumer touchpoints
- Algorithmic Vision: Lead the development of ML solutions and ranking frameworks that power our discovery canvases. You will move beyond local optimizations to solve for long-term ecosystem health and user retention
- Strategic XFN Partnership: Act as the primary scientific advisor to Product and Engineering leaders. You will use data to inform, drive, and accelerate innovations via deep-dive insights and ML prototypes
- Causal Inference & Experimentation: Leverage advanced causal inference methodologies to measure the effectiveness of platform initiatives (e.g., social features or site-wide events) that are often susceptible to complex network effects
- Foundational Scaling: Develop frameworks to scale the hypothesis generation process, ensuring that our experimentation velocity matches our massive growth
- First-Principles Problem Solving: Apply creative, first-principles reasoning to ambiguous problems, such as balancing the visibility of established “top tier” experiences with the discovery of new, niche UGC content
- Ability to design sophisticated experiments that account for the nuances of a two-sided marketplace and social network effects
- Ability to distill high-dimensional problems into succinct, actionable narratives for non-technical executive audiences
- Expert in the modern data stack (Python, R, SQL, Hive, Spark, Airflow) and have a deep theoretical and practical understanding of Deep Learning
- Advanced degree (Masters or PhD) in a quantitative field (Statistics, CS, Physics, Applied Math, or Economics)
- 4+ years of experience (or 2+ with a PhD) in Data Science, Economics, or ML Engineering, specifically within large-scale recommendation systems or UGC content platforms.